检索结果-内蒙古大学图书馆

IEEE Latin American Robotics Symposium, LARS

作者： João Alberto Fabro Matheus Biscaya Gutierrez Fernando Henrique Ratusznei Caetano DAINF - Academic Department of Informatica PPGCA - Graduate Program on Applied Computing LASER-Laboratory for Advanced Robotics and Embedded Systems UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Information Systems academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Computer Engineering academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

In this paper, an approach to aid in introductory programming courses is presented, focused on students that had never had any contact with computer programming. The approach, that was introduced in a previous paper [3], presents programming concepts using icons and “flowcharts”, and a 3D robotics simulator (CoppeliaSim), that has free educational use. This time, a real version of the simulated robot, built using Arduino and cheap, easily obtainable electronic components, is also presented. The programs to control the robot are developed by graphically constructing flowcharts on the visual editor, and then following the execution of programs using the simulated (or real) robot, step by step. This graphic program editor is named “FluxProg”, and its 2nd version is now available online, with new features comprising variables, arithmetic and logic expressions, thus providing a complete programming environment.

关键词： Flowcharts Visualization Three-dimensional displays Conferences Education Electronic components Robots

来源：评论

学校读者我要写书评

暂无评论

Machine learning techniques in bank credit analysis of companies: A case study of a Brazilian bank 49

Machine learning techniques in bank credit analysis of compa...

引用

49th International Conference on Computers and Industrial engineering, CIE 2019

作者： Assef, F.M. Steiner, M.T.A. Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Paraná Curitiba Brazil

The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, not always did the best accuracy represent the best technique for the assessment of this problem. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study. © 2019, Computers and Industrial engineering. All rights reserved.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Scalable Crystal Structure Relaxation Using an Iteration-Free Deep Generative Model with Uncertainty Quantification

arXiv

引用

arXiv 2024年

作者： Yang, Ziduo Zhao, Yi-Ming Wang, Xian Liu, Xiaoqing Zhang, Xiuying Li, Yifan Lv, Qiujie Chen, Calvin Yu-Chian Shen, Lei Department of Mechanical Engineering National University of Singapore Singapore117575 Singapore Artificial Intelligence Medical Research Center School of Intelligent Systems Engineering Shenzhen Campus of Sun Yat-sen University Shenzhen518107 China Department of Physics National University of Singapore Singapore117551 Singapore -Preferred Program School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen518055 China State Key Laboratory of Chemical Oncogenomics School of Chemical Biology and Biotechnology Peking University Shenzhen Graduate School Shenzhen518055 China Department of Medical Research China Medical University Hospital Taichung40447 Taiwan Department of Bioinformatics and Medical Engineering Asia University Taichung41354 Taiwan Guangdong L-Med Biotechnology Co. Ltd. Guangdong Meizhou514699 China Research Institute Chongqing401123 China

In computational molecular and materials science, determining equilibrium structures is the crucial first step for accurate subsequent property calculations. However, the recent discovery of millions of new crystals and complex twisted structures has challenged traditional computational methods, both ab initio and machine-learning-based, due to their computationally intensive iterative processes. To address these scalability issues, here we introduce DeepRelax, a deep generative model capable of performing geometric crystal structure relaxation rapidly and without iterations. DeepRelax learns the equilibrium structural distribution, enabling it to predict relaxed structures directly from their unrelaxed ones. The ability to perform structural relaxation at the millisecond level per structure, combined with the scalability of parallel processing, makes DeepRelax particularly useful for large-scale virtual screening. We demonstrate DeepRelax's reliability and robustness by applying it to five diverse databases, including oxides, Materials Project, two-dimensional materials, van der Waals crystals, and crystals with point defects. DeepRelax consistently shows high accuracy and efficiency, validated by density functional theory calculations. Finally, we enhance its trustworthiness by integrating uncertainty quantification. This work significantly accelerates computational workflows, offering a robust and trustworthy machine-learning method for material discovery and advancing the application of AI for science. Code for DeepRelax is available at https://***/Shen-Group/DeepRelax. Copyright © 2024, The Authors. All rights reserved.

关键词： Point defects

来源：评论

学校读者我要写书评

暂无评论

Speaker-Specific Articulatory Feature Extraction Based on Knowledge Distillation for Speaker Recognition

引用

APSIPA Transactions on Signal and Information Processing 2023年第2期12卷

作者： Qian-Bei Hong Hsin-Min Wang Chung-Hsien Wu Graduate Program of Multimedia Systems and Intelligent Computing National Cheng Kung University and Academia Sinica Taiwan Graduate Program of Multimedia Systems and Intelligent Computing National Cheng Kung University and Academia Sinica and Department of Computer Science and Information Engineering National Cheng Kung University Taiwan

This paper proposes a novel speaker-specific articulatory feature (AF) extraction model based on knowledge distillation (KD) for speaker recognition. First, an AF extractor is trained as a teacher model for extracting the AF profiles of the input speaker dataset. Next, a KD-based speaker embedding extraction method is proposed to distill the speaker-specific information from the AF profiles in the teacher model to a student model based on multi-task learning, in which the lower layers not only capture the speaker characteristics from acoustic features, but also learn the speaker-specific features from the AF profiles for robust speaker representation. Finally, speaker embeddings are extracted from the high-level layer, and the obtained speaker embeddings are further used to train a probabilistic linear discriminant analysis (PLDA) model for speaker recognition. In the experiments, speaker embedding models were trained using the VoxCeleb2 dataset and the AF extractor was trained based on the LibriSpeech dataset, and the performance was evaluated using the VoxCeleb1 dataset. The experiments showed that the proposed KD-based models outperformed the baseline models without KD. Furthermore, feature concatenation of multimodal results can further improve the performance.

关键词： Speaker recognition articulatory feature knowledge distillation

来源：评论

学校读者我要写书评

暂无评论

An Approach to Semantic Interoperability for Product Development Through Automatic Requirement Extraction and Semantic Reconciliation 16th

An Approach to Semantic Interoperability for Product Develop...

引用

16th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2019

作者： Canciglieri, Matheus Beltrame de Moura Leite, Athon Francisco Curi Staben Szejka, Anderson Luis Junior, Osiris Canciglieri Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil

ISBN: (纸本)9783030422493

The strong competitiveness challenges manufacturing industry to rationalize different ways of bringing new products to the market in the shortest time with competitive prices while ensuring higher quality. Industries need to effectively share product requirements, which comes from various sources and are heterogeneous in nature, during the Product Development Process (PDP) to stay competitive. However, problems with misinterpretation of such requirements have been identified during its sharing due to semantic interoperability obstacles related to the process of automatically gathering requirements and their translation and reuse. This research proposes an approach to automatically gather product requirements, extracting its knowledge and translate it for further use and reuse along PDP. The research structure consisted of firstly studying the current issues of the topic, secondly by exploring an approach, to be validated in an experimental case. Current issues point out to gaps related to the process of semantic reconciliation and knowledge extraction perspectives, giving it a multi-dimensional panorama where semantic issues are intertwined among different perspectives. The later solution presents an approach which considers raw information being processed into product features, refining knowledge during PDP and making it reusable in different cycles. The approach brings a new view on practical methods for automatically collect product requirements, extract its knowledge and translate it into product features, based on knowledge extraction methods and by using semantic reconciliation as means for translating product’s requirements. Further research will focus on expanding the approach and including more features to increasingly complex cases, to explore the full potential of the approach. © 2019, IFIP International Federation for Information Processing.

关键词： Product design

来源：评论

学校读者我要写书评

暂无评论

Computer Vision with Cognitive Learning to Improve the Decision-Making During the Sales Process in Physical Stores 16th

Computer Vision with Cognitive Learning to Improve the Decis...

引用

16th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2019

作者： da Silva Ramalho, Vinícius Szejka, Anderson Luis Rudek, Marcelo Junior, Osiris Canciglieri Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil

ISBN: (纸本)9783030422493

In a world where the information is obtained faster than ever seem, new methods to process that high volume of data are being developed frequently. This is more notorious in a virtual ambient where the data is generated in a manner that is faster and easier to analyze than in the real world. This is very evident in the retail field, where virtual stores have easy access to all the advertisement a user visited and simple to obtain user profile, on the other hand physical stores are limited to basically create a register in a database when there is a purchase. In an attempt to improve the retailers experience from physical stores to manage their business this document has the objective to develop a computational tool that will analyze the people flux going in the establishment, trying to inform the retailer the amount of people and their gender to help the sales process in physical stores. To this end, computational vision methods and algorithms were raised, which after selection, theoretical conception and tool’s implementation it was tested with benchmarks to operate locally and in real time by accessing the cameras installed strategically in a real scenario. Two scenarios were tested: static ambient light and dynamic light. Two tests were conducted: YOLOv2 against background subtraction-based counter;gender classification using full body features. Even though the results were not as positive as needed for commercial use, the tool demonstrated potential and space for improvements. © 2019, IFIP International Federation for Information Processing.

关键词： Computer vision

来源：评论

学校读者我要写书评

暂无评论

Technology Roadmap for Flexible Sensors

引用

ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

来源：评论

学校读者我要写书评

暂无评论

Water management and conductivity studies in novel polymer zirconium-based membranes for PEM fuel cells

引用

Case Studies in Chemical and Environmental engineering 2025年 11.0卷

作者： Ahmed, Tallah Magdi Al Othman, Amani Shamayleh, Abdulrahim Tawalbeh, Muhammad Engineering Systems Management Graduate Program American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Department of Chemical and Biological Engineering American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Energy Water and Sustainable Environment Research Center American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Department of Industrial Engineering American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Sustainable and Renewable Energy Engineering Department University of Sharjah PO. Box 27272 Sharjah United Arab Emirates Sustainable Energy & Power Systems Research Centre RISE University of Sharjah P.O. Box 27272 Sharjah United Arab Emirates

Proton exchange membrane fuel cells (PEMFCs) are among the promising alternatives for clean energy generation, especially when hydrogen is the fuel used. Their operation is still faced with several challenges, and one of them is water accumulation in the cathode compartment. If PEMFCs are operated at temperatures above the boiling point of water, a significant obstacle would be eliminated due to the formation of water in the vapor phase. This prevents water from accumulating in the liquid phase which causes flooding. Therefore, this work aims to develop a novel composite membrane based on zirconium silicate (ZrSiO₄) and Polyvinylidene fluoride (PVDF) for such high-temperature operation. The composite membrane was synthesized using solution casting, and its structural and chemical properties were characterized using thermogravimetric analysis (TGA), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) techniques. The ZrSiO₄/PVDF membrane demonstrated a maximum proton conductivity of 2.14 × 10⁻³ S/cm at room temperature with 8 wt% ZrSiO₄, along with a water uptake value of 43.85 %. Consequently, when tested above the boiling point of water, the membrane exhibited a high conductivity of 2.13 × 10⁻³ S/cm at 105 °C. The results suggest the suitability of such zirconium silicate-based composite membranes for fuel cell applications operating above the boiling point of water. © 2024 The Author(s)

关键词： Composite membranes PEM fuel cells Proton conduction PVDF Water management Zirconium silicate

来源：评论

学校读者我要写书评

暂无评论

Diesel/Biodiesel/Biogas Mixtures Driven Compression Ignition Internal Combustion Engines Constructal Design

SSRN

引用

SSRN 2024年

作者： Arcanjo, S. Vargas, José Viriato Coelho Ordonez, J.C. Och, S.H. Balmant, W. Mariano, A.B. Kava, V.M. Department of Mechanical Engineering Graduate Program in Mechanical Engineering PGMEC andSustainableEnergyResearch&DevelopmentCenter NPDEAS FederalUniversityofParaná UFPR CP 19011 PR Curitiba81531–980 Brazil Department of Mechanical Engineering Energy and Sustainability Center Center for Advanced Power Systems Florida State University FSU TallahasseeFL32310–6046 United States Department of Electrical Engineering Sustainable Energy Research & Development Center NPDEAS Federal University of Paraná UFPR CP 19011 PR Curitiba81531–980 Brazil Department of Genetics Sustainable Energy Research & Development Center NPDEAS Federal University of Paraná UFPR CP 19011 PR Curitiba81531–980 Brazil

This paper introduces a first and second law based transient mathematical model for 4-stroke compression ignition internal combustion engines (CI-ICE) driven by diesel/biodiesel/biogas mixtures to allow for the maximization of system performance. In this way, the CI-ICE morphology that provides easier access to the currents that flow through it is sought, according to constructal law. The total entropy generated in the CI-ICE cycle was calculated by adding the entropy generation in all strokes. An optimization problem was formulated based on the variation of operating and geometric parameters, and the objective functions were the effective and 2nd law efficiencies, and , as well as the destroyed exergy fraction, . The optimal ranges found for the bore-stroke, compression and conrod-crank ratios were;, and in which with for D100 (pure diesel), and with for B50D25NG25 (biodiesel/diesel/natural gas blend). The maxima and minimum found were sharp, since and varied up to 71% and 69% in comparison to their maximum values, respectively, and up to 45% in comparison to its minimum value within the adopted ranges of variation of the optimized parameters. Such large variations stress the importance of considering the optimized CI-ICE morphology in actual design, i.e., CI-ICE constructal design. © 2024, The Authors. All rights reserved.

关键词： Entropy

来源：评论

学校读者我要写书评

暂无评论

The Impact of Covid-19 on Happiness: Changed Psychological and Attitudinal Characteristics

SSRN

引用

SSRN 2022年

作者： Park, Yunmi Gim, Tae-Hyoung Tommy Architectural and Urban Systems Engineering College of Engineering Ewha Womans University #509 Asan Engineering Bldg. 52 Ewhayeodae-gil Seodaemun-gu Seoul03760 Korea Republic of Graduate School of Environmental Studies Interdisciplinary Program in Landscape Architecture Environmental Planning Institute Seoul National University #222 Building 82 Gwanak-ro 1 Gwanak-gu Seoul08826 Korea Republic of

COVID-19 has had a considerable negative influence on subjective well-being. It has also been claimed that a decline in happiness has resulted from forced changes in psychological and attitudinal status (e.g., working from home, risk perception, or compactness preference) during the global pandemic. This study sought to empirically examine this association using a nationwide survey conducted in the United States in 2020. Socio-demographic life circumstances, COVID-19 restrictions, travel modes, and psychological and attitudinal characteristics were defined with 75 items to detail the story of happiness during the pandemic. The findings showed that socio-demographic factors contributed to the majority of happiness but that perceived infection risk of close relationships, restricted social interactions and activities, high infection risk perception, avoidance of online alternatives, and decreased compactness preference all contributed to reduced happiness. In particular, job, income level, and modes of transportation before COVID-19 also affected the level of happiness during COVID-19. © 2022, The Authors. All rights reserved.

关键词： Risk perception

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：